DBMS > Databricks vs. NSDb vs. Sadas Engine vs. ToroDB

System Properties Comparison Databricks vs. NSDb vs. Sadas Engine vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Document store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

www.databricks.com

nsdb.io

www.sadasengine.com

github.com/torodb/server

Technical documentation

docs.databricks.com

nsdb.io/Architecture

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Databricks

SADAS s.r.l.

8Kdata

Initial release

2013

2017

2006

2016

Current release

8.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free trial version available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Scala

C++

Java

Server operating systems

hosted

Linux
macOS

AIX
Linux
Windows

All OS with a Java 7 VM

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

yes

string, integer, double, boolean, date, object_id

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

with Databricks SQL

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

JDBC
ODBC
Proprietary protocol

Supported programming languages

Python
R
Scala

Java
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

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